A number of personal tracking systems are available that can be used to track or monitor the position of a person. Users of such systems can include elderly people, children, people with Alzheimer's disease, dementia or autism (who are prone to wandering) or patients in a care home or hospital. A ‘geofence’ may be established that bounds safe or acceptable areas in which the user is allowed to move freely, such as in their home, or conversely areas that the user should not enter, and the tracking system can be used to verify whether the user is within their safe zone or geographical fence, and if not, trigger an alarm and determine the position of the user.
These systems typically comprise a user-worn or user-carried device and a base unit that is placed in (and helps to define) the safe zone. The user device can include a GPS receiver in combination with another wireless communication technology, such as cellular communications or WiFi, that is used to monitor the position of the user. However, these systems are hindered by either poor performance due to low location sampling rates (to conserve power), poor battery life (if the sampling rate is set higher) or have a significant size due to inclusion of a large battery in the device.
In some cases the base unit can act as a beacon for the user device, and the user device can use signals sent from the base unit to determine whether the user device (and thus the user) is within the safe zone. Some devices use a measurement of the received signal strength (for example a measurement of the power in a received radio signal, known as a Received Signal Strength Indicator, RSSI) to estimate the distance from the base unit and thus determine whether the user device is within the safe zone. This technique can often consume less power than other location-estimating technologies such as GPS. However, distance estimation based on signal strength measurements is not very robust and either produces inconsistent or erratic distance measurements or requires assistance from another location-determining technology such as GPS or triangulation using cellular base stations.
In particular, it has been found that RSSI-based distance detection devices produce inconsistent distance results as the orientation of the user and/or user device changes with respect to the base unit. This is illustrated in FIG. 1. In this Figure, a user 2 that is carrying a user device 4 is shown at two different distances from and orientations with respect to a base unit 6. In the first distance and orientation (labelled ‘A’), the user 2 and user device 4 are oriented such that there is line of sight from the user device 4 to the base unit 6 which results in the user device 4 receiving a relatively strong signal from the base unit. This orientation of the user 2 and user device 4 can provide a reasonably reliable estimate of the distance between the user device 4 and the base unit 6 using signal strength measurements. However, in the second distance and orientation (labelled ‘B’), the user 2 is much closer to the base unit 6 but there is no line of sight between the user device 4 and the base unit 6 as it is blocked/shielding by the body of the user 2. This shielding of the user device 4 by the body of the user 2 attenuates the strength of the signal received from the base unit 6 by many decibels and thus leads the user device 4 to determine that the user device 4 is further from the base unit 6 than is in fact the case (and it may even be determined that the user 2 is outside the determined safe zone depending on the level of attenuation).
In addition, objects in and the materials used to construct the home or healthcare environment of the user can affect the strength of the received signals.
An alternative technique for determining the distance between a user device and a base unit is based on the time-of-flight (ToF) of signals between the user device and base unit. This technique is much more robust against signal attenuation. Generally, time of flight measurements are based on signals transmitted in the ultra wideband, UWB range (2.4-5 GHz) because the accuracy that can be achieved is dependent on the amount of bandwidth that is available and the signal to noise ratio (according to the Cramer-Rao limit). However, a disadvantage of UWB time-of-flight or time-of-flight in the GHz range is the limited range of the transmissions (when keeping power consumption down) or high energy consumption of the user device (when trying to increase the range).
Thus, it is desirable to perform time-of-flight measurements using narrowband communications (for example in the 900 MHz range) since less power is required and the range is improved over UWB, and sub-meter accuracies have been shown for such systems. However, a large number of messages need to be exchanged between the user device and base unit in order to produce an accurate result, but this results in additional power consumption and in some countries and/or specifications there are regulatory limits on the total time the transmitter is allowed to be active (e.g. at most 10% of the time).
There is therefore a need for an improved technique for performing a time-of-flight-based distance measurement that can provide a distance measurement to a desired level of accuracy while minimising power consumption and that is suitable for use in a personal tracking system to determine whether a user is within a predetermined safe zone.